Agentic AI Is Easy: Running It in Production Is Not

Most agentic AI systems work well in demo environments. Far fewer survive production.

In this whitepaper, Microland's Chief AI Officer Alok Shrivastwa draws on direct experience building and operating Agentic AI-based use cases for enterprise infrastructure to explain why that gap exists and how to close it. The paper identifies four structural failure modes common to production deployments: silent failure, black box decisions, permission explosion, and runaway execution. It then introduces a deterministic four-stage control architecture that separates intent interpretation, policy authorization, context validation, and zero-trust credential issuance into independently enforceable stages.

For CIOs and technology leaders preparing to scale Agentic AI, this paper provides both the diagnostic framework and the architectural blueprint to do it safely.